945 resultados para Aerial tramways.
Resumo:
Liquid chromatography/mass spectrometry (MS)/MS was used to analyse toxins in P. trichostachia, P. simplex subsp. continua, P. simplex subsp. continua and P. elongata samples (flowers, seeds, branches, main stem, leaves and roots) collected from various locations in Queensland, Saskatchewan and New South Wales, Australia. Simplexin was the major analyte in all taxa, with varying minor levels of huratoxin. Simplexin levels in P. trichostachia and P. elongata were higher (580 and 540 mg/kg in flowering foliage, respectively) than in P. simplex (255 mg/kg). Levels of huratoxin were higher in P. simplex (relative to simplexin) than in P. trichostachia or P. elongata. P. simplex flower heads and roots contained similar simplexin levels, with very small amounts of toxins detected in branches, stems and leaves. In P. trichostachia, simplexin levels were high in flower heads but low in the the other plant parts. The simplexin levels in aerial parts were generally higher from the pre-flowering to the flowering stage, decreasing towards the post-flowering stage; similar trends were recorded for P.elongata samples collected from a site near Bollon and P. trichostachia samples collected from a site near Jericho (both sites in Queensland). The simplexin concentration in roots was much less variable. Flowers and seeds had much higher simplexin levels than the foliage. The breakdown of the toxin in litter was more rapid compared to seeds under the same weathering conditions. Unlike the results from the litter samples, no significant decrease occurred in seed samples after 18 months of exposure.
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Fractionation of methanolic extracts of air dried aerial parts ofParthenium resulted in the isolation of a toxic constituent which was identified as parthenin, the major sesquiterpene lactone from the weed. The LD50 (minimal lethal dose required to cause 50% mortality) for parthenin in rats was 42 mg/kg body weight. When [3H]-parthenin was given orally or by intravenous administration, radioactivity appeared in the milk of lactating laboratory and dairy animals. Tissue distribution of radioactivity revealed that maximum label was detectable in kidneys.
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This thesis examines the feasibility of a forest inventory method based on two-phase sampling in estimating forest attributes at the stand or substand levels for forest management purposes. The method is based on multi-source forest inventory combining auxiliary data consisting of remote sensing imagery or other geographic information and field measurements. Auxiliary data are utilized as first-phase data for covering all inventory units. Various methods were examined for improving the accuracy of the forest estimates. Pre-processing of auxiliary data in the form of correcting the spectral properties of aerial imagery was examined (I), as was the selection of aerial image features for estimating forest attributes (II). Various spatial units were compared for extracting image features in a remote sensing aided forest inventory utilizing very high resolution imagery (III). A number of data sources were combined and different weighting procedures were tested in estimating forest attributes (IV, V). Correction of the spectral properties of aerial images proved to be a straightforward and advantageous method for improving the correlation between the image features and the measured forest attributes. Testing different image features that can be extracted from aerial photographs (and other very high resolution images) showed that the images contain a wealth of relevant information that can be extracted only by utilizing the spatial organization of the image pixel values. Furthermore, careful selection of image features for the inventory task generally gives better results than inputting all extractable features to the estimation procedure. When the spatial units for extracting very high resolution image features were examined, an approach based on image segmentation generally showed advantages compared with a traditional sample plot-based approach. Combining several data sources resulted in more accurate estimates than any of the individual data sources alone. The best combined estimate can be derived by weighting the estimates produced by the individual data sources by the inverse values of their mean square errors. Despite the fact that the plot-level estimation accuracy in two-phase sampling inventory can be improved in many ways, the accuracy of forest estimates based mainly on single-view satellite and aerial imagery is a relatively poor basis for making stand-level management decisions.
Resumo:
The use of remote sensing imagery as auxiliary data in forest inventory is based on the correlation between features extracted from the images and the ground truth. The bidirectional reflectance and radial displacement cause variation in image features located in different segments of the image but forest characteristics remaining the same. The variation has so far been diminished by different radiometric corrections. In this study the use of sun azimuth based converted image co-ordinates was examined to supplement auxiliary data extracted from digitised aerial photographs. The method was considered as an alternative for radiometric corrections. Additionally, the usefulness of multi-image interpretation of digitised aerial photographs in regression estimation of forest characteristics was studied. The state owned study area located in Leivonmäki, Central Finland and the study material consisted of five digitised and ortho-rectified colour-infrared (CIR) aerial photographs and field measurements of 388 plots, out of which 194 were relascope (Bitterlich) plots and 194 were concentric circular plots. Both the image data and the field measurements were from the year 1999. When examining the effect of the location of the image point on pixel values and texture features of Finnish forest plots in digitised CIR photographs the clearest differences were found between front-and back-lighted image halves. Inside the image half the differences between different blocks were clearly bigger on the front-lighted half than on the back-lighted half. The strength of the phenomenon varied by forest category. The differences between pixel values extracted from different image blocks were greatest in developed and mature stands and smallest in young stands. The differences between texture features were greatest in developing stands and smallest in young and mature stands. The logarithm of timber volume per hectare and the angular transformation of the proportion of broadleaved trees of the total volume were used as dependent variables in regression models. Five different converted image co-ordinates based trend surfaces were used in models in order to diminish the effect of the bidirectional reflectance. The reference model of total volume, in which the location of the image point had been ignored, resulted in RMSE of 1,268 calculated from test material. The best of the trend surfaces was the complete third order surface, which resulted in RMSE of 1,107. The reference model of the proportion of broadleaved trees resulted in RMSE of 0,4292 and the second order trend surface was the best, resulting in RMSE of 0,4270. The trend surface method is applicable, but it has to be applied by forest category and by variable. The usefulness of multi-image interpretation of digitised aerial photographs was studied by building comparable regression models using either the front-lighted image features, back-lighted image features or both. The two-image model turned out to be slightly better than the one-image models in total volume estimation. The best one-image model resulted in RMSE of 1,098 and the two-image model resulted in RMSE of 1,090. The homologous features did not improve the models of the proportion of broadleaved trees. The overall result gives motivation for further research of multi-image interpretation. The focus may be improving regression estimation and feature selection or examination of stratification used in two-phase sampling inventory techniques. Keywords: forest inventory, digitised aerial photograph, bidirectional reflectance, converted image coordinates, regression estimation, multi-image interpretation, pixel value, texture, trend surface
Resumo:
Selenium (Se) has been demonstrated to be an essential trace element for maintenance of animal and human health. Although it has not been confirmed to be an essential micronutrient in higher plants, there is increasing evidence that Se functions as an antioxidant in plants. Selenium has been shown to exert a beneficial effect on crop growth and promotes stress tolerance at low concentrations. However, the specific physiological mechanisms that underlie the positive effects of Se in plants have not been clearly elucidated. The aims of this study were to determine the Se concentration in potato (Solanum tuberosum L.) and the effects of Se on the accumulation of carbohydrates, growth and yield in potato plants. An additional aim was to study the impact of Se on the total glycoalkaloid concentration in immature potato tubers. The distribution of Se in different biochemical Se fractions and the effect of storage on the Se concentration were studied in Se-enriched tubers. Furthermore, the effect of Se on raw darkening and translocation of Se from seed tubers to the next tuber generation was investigated. Due to the established anti-ageing properties of Se, it was of interest to study if Se affects physiological age and growth vigour of seed tubers. The Se concentrations in the upper leaves, roots, stolons and tubers of potato increased with increasing Se supplementation. The highest Se concentration was reached in young upper leaves, roots and stolons, indicating that added selenate was efficiently utilized and taken up at an early stage. During the growing period the Se concentration declined in the aerial parts, roots and stolons of potato plants whereas an intensive accumulation took place in immature and mature tubers. Selenium increased carbohydrate accumulation in the young upper leaves and in stolons, roots and tubers at maturity. This could not be explained by increased production of photoassimilates as net photosynthesis did not differ among Se treatments. The Se treated plants produced higher tuber yields than control plants, and at the highest Se concentration (0.3 mg kg-1) lower numbers of larger tubers were harvested. Increased yield of Se treated plants suggested that Se may enhance the allocation of photoassimilates for tuber growth, acting as a strong sink for both Se and for carbohydrates. Similarly as for other plant species, the positive impact of Se on the yield of potato plants could be related to its antioxidative effect in delaying senescence. The highest Se supplementation (0.9 mg kg-1) slightly decreased the glycoalkaloid concentration of immature tubers. However, at this level the Se concentration in tubers was about 20 µg g-1 DW. A 100 g consumption of potato would provide about 500 mg of Se, which exceeds the upper safe intake level of 400 µg per day for human dietary. The low Se applications (0.0035 and 0.1 mg kg-1) diminished and retarded the degree of raw darkening in tubers stored for one and eight months, which can be attributed to the antioxidative properties of Se. The storage for 1 to 12 months did not affect the Se concentrations of tubers. In the Se enriched tubers Se was allocated to the organic Se fraction, indicating that it was incorporated into organic compounds in tubers. Elevated Se concentration in the next-generation tubers produced by the Se enriched seed tubers indicated that Se could be translocated from the seed tubers to the progeny. In the seed tubers stored for 8 months, at high levels, Se had some positive effects on the growth vigour of sprouts, but Se had no consistent effect on the growth vigour of seed tubers of optimal physiological age. These results indicate that Se is a beneficial trace element in potato plants that exerts a positive effect on yield formation and improves the processing and storage quality of table potato tubers. These positive effects of Se are, however, dependent on the Se concentration and the age of the potato plant and tuber.
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There is an increased interest on the use of Unmanned Aerial Vehicles (UAVs) for wildlife and feral animal monitoring around the world. This paper describes a novel system which uses a predictive dynamic application that places the UAV ahead of a user, with a low cost thermal camera, a small onboard computer that identifies heat signatures of a target animal from a predetermined altitude and transmits that target’s GPS coordinates. A map is generated and various data sets and graphs are displayed using a GUI designed for easy use. The paper describes the hardware and software architecture and the probabilistic model for downward facing camera for the detection of an animal. Behavioral dynamics of target movement for the design of a Kalman filter and Markov model based prediction algorithm are used to place the UAV ahead of the user. Geometrical concepts and Haversine formula are applied to the maximum likelihood case in order to make a prediction regarding a future state of the user, thus delivering a new way point for autonomous navigation. Results show that the system is capable of autonomously locating animals from a predetermined height and generate a map showing the location of the animals ahead of the user.
Resumo:
There is an increased interest on the use of UAVs for environmental research such as tracking bush fires, volcanic eruptions, chemical accidents or pollution sources. The aim of this paper is to describe the theory and results of a bio-inspired plume tracking algorithm. A method for generating sparse plumes in a virtual environment was also developed. Results indicated the ability of the algorithms to track plumes in 2D and 3D. The system has been tested with hardware in the loop (HIL) simulations and in flight using a CO2 gas sensor mounted to a multi-rotor UAV. The UAV is controlled by the plume tracking algorithm running on the ground control station (GCS).
Resumo:
There is an increased interest in the use of Unmanned Aerial Vehicles for load transportation from environmental remote sensing to construction and parcel delivery. One of the main challenges is accurate control of the load position and trajectory. This paper presents an assessment of real flight trials for the control of an autonomous multi-rotor with a suspended slung load using only visual feedback to determine the load position. This method uses an onboard camera to take advantage of a common visual marker detection algorithm to robustly detect the load location. The load position is calculated using an onboard processor, and transmitted over a wireless network to a ground station integrating MATLAB/SIMULINK and Robotic Operating System (ROS) and a Model Predictive Controller (MPC) to control both the load and the UAV. To evaluate the system performance, the position of the load determined by the visual detection system in real flight is compared with data received by a motion tracking system. The multi-rotor position tracking performance is also analyzed by conducting flight trials using perfect load position data and data obtained only from the visual system. Results show very accurate estimation of the load position (~5% Offset) using only the visual system and demonstrate that the need for an external motion tracking system is not needed for this task.
Resumo:
Context. The feral pig (Sus scrofa) is a widespread pest species in Australia and its populations are commonly controlled to reduce damage to agriculture and the environment. Feral pigs are also a resource and harvested for commercial export as game meat. Although many other control techniques are used, commercial harvesting of feral pigs is often encouraged by land managers, because it carries little or no cost and is widely perceived to control populations. Aims. To use feral-pig harvesting records, density data and simple harvest models to examine the effectiveness of commercial harvesting to reduce feral-pig populations. Methods. The present study examined commercial harvest off-take on six sites (246-657 km2) in southern Queensland, and 20 large blocks (~2-6000 km2) throughout Queensland. The harvest off-take for each site was divided by monthly or average annual population size, determined by aerial survey, to calculate monthly and annual harvest rates.Asimple harvest model assuming logistic population growth was used to determine the likely effectiveness of harvesting. Key results. Commercial harvest rates were generally low (<~20%) and are likely to provide only modest reductions in population size. Additionally, harvest rates capable of substantial reductions (>50%) in long-term population size were isolated occurrences and not maintained across sites and years. High harvest rates were observed only at low densities. Although these harvest rates may be sufficiently high to hold populations at low densities, the population is likely to escape this entrapment following a flush in food supply or a reduction in harvest effort. Implications. Our results demonstrated that, at current harvest rates, commercial harvesting is ineffective for the landscape-scale control of feral-pig populations. Unless harvest rates can be significantly increased, commercial harvesting should be used as a supplement to, rather than as a substitute for, other damage-control techniques.
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Due to the recent development in CCD technology aerial photography is now slowly changing from film to digital cameras. This new aspect in remote sensing allows and requires also new automated analysis methods. Basic research on reflectance properties of natural targets is needed so that computerized processes could be fully utilized. For this reason an instrument was developed at Finnish Geodetic Institute for measurement of multiangular reflectance of small remote sensing targets e.g. forest understorey or asphalt. Finnish Geodetic Institute Field Goniospectrometer (FiGIFiGo) is a portable device that is operated by 1 or 2 persons. It can be reassembled to a new location in 15 minutes and after that a target's multiangular reflectance can be measured in 10 - 30 minutes (with one illumination angle). FiGIFiGo has effective spectral range approximately from 400 nm to 2000 nm. The measurements can be made either outside with sunlight or in laboratory with 1000 W QTH light source. In this thesis FiGIFiGo is introduced and the theoretical basis of such reflectance measurements are discussed. A new method is introduced for extraction of subcomponent proportions from reflectance of a mixture sample, e.g. for retrieving proportion of lingonberry's reflectance in observation of lingonberry-lichen sample. This method was tested by conducting a series of measurements on reflectance properties of artificial samples. The component separation method yielded sound results and brought up interesting aspects in targets' reflectances. The method and the results still need to be verified with further studies, but the preliminary results imply that this method could be a valuable tool in analysis of such mixture samples.
Resumo:
The ubiquitous fungal pathogen Macrophomina phaseolina is best known as causing charcoal rot and premature death when host plants are subject to post-flowering stress. Overseas reports of M.phaseolina causing a rapid rot during the sprouting of Australian mungbean seed resulted in an investigation of the possible modes of infection of seed. Isolations from serial portions of 10 mungbean plants naturally infected with the pathogen revealed that on most plants there were discrete portions of infected tissue separated by apparently healthy tissue. The results from these studies, together with molecular analysis of isolates collected from infected tissue on two of the plants, suggested that aerial infection of aboveground parts by different isolates is common. Inoculations of roots and aboveground parts of mungbean plants at nine temperaturexsoil moisture incubation combinations and of detached green pods strongly supported the concept that seed infection results from infection of pods by microsclerotia, rather than from hyphae growing systemically through the plant after root or stem infection. This proposal is reinforced by anecdotal evidence that high levels of seed infection are common when rainfall occurs during pod fill, and by the isolation of M.phaseolina from soil peds collected on pods of mungbean plants in the field. However, other experiments showed that when inoculum was placed within 130mm of a green developing pod and a herbicide containing paraquat and diquat was sprayed on the inoculated plants, M.phaseolina was capable of some systemic growth from vegetative tissue into the pods and seeds.
Resumo:
This thesis presents novel modelling applications for environmental geospatial data using remote sensing, GIS and statistical modelling techniques. The studied themes can be classified into four main themes: (i) to develop advanced geospatial databases. Paper (I) demonstrates the creation of a geospatial database for the Glanville fritillary butterfly (Melitaea cinxia) in the Åland Islands, south-western Finland; (ii) to analyse species diversity and distribution using GIS techniques. Paper (II) presents a diversity and geographical distribution analysis for Scopulini moths at a world-wide scale; (iii) to study spatiotemporal forest cover change. Paper (III) presents a study of exotic and indigenous tree cover change detection in Taita Hills Kenya using airborne imagery and GIS analysis techniques; (iv) to explore predictive modelling techniques using geospatial data. In Paper (IV) human population occurrence and abundance in the Taita Hills highlands was predicted using the generalized additive modelling (GAM) technique. Paper (V) presents techniques to enhance fire prediction and burned area estimation at a regional scale in East Caprivi Namibia. Paper (VI) compares eight state-of-the-art predictive modelling methods to improve fire prediction, burned area estimation and fire risk mapping in East Caprivi Namibia. The results in Paper (I) showed that geospatial data can be managed effectively using advanced relational database management systems. Metapopulation data for Melitaea cinxia butterfly was successfully combined with GPS-delimited habitat patch information and climatic data. Using the geospatial database, spatial analyses were successfully conducted at habitat patch level or at more coarse analysis scales. Moreover, this study showed it appears evident that at a large-scale spatially correlated weather conditions are one of the primary causes of spatially correlated changes in Melitaea cinxia population sizes. In Paper (II) spatiotemporal characteristics of Socupulini moths description, diversity and distribution were analysed at a world-wide scale and for the first time GIS techniques were used for Scopulini moth geographical distribution analysis. This study revealed that Scopulini moths have a cosmopolitan distribution. The majority of the species have been described from the low latitudes, sub-Saharan Africa being the hot spot of species diversity. However, the taxonomical effort has been uneven among biogeographical regions. Paper III showed that forest cover change can be analysed in great detail using modern airborne imagery techniques and historical aerial photographs. However, when spatiotemporal forest cover change is studied care has to be taken in co-registration and image interpretation when historical black and white aerial photography is used. In Paper (IV) human population distribution and abundance could be modelled with fairly good results using geospatial predictors and non-Gaussian predictive modelling techniques. Moreover, land cover layer is not necessary needed as a predictor because first and second-order image texture measurements derived from satellite imagery had more power to explain the variation in dwelling unit occurrence and abundance. Paper V showed that generalized linear model (GLM) is a suitable technique for fire occurrence prediction and for burned area estimation. GLM based burned area estimations were found to be more superior than the existing MODIS burned area product (MCD45A1). However, spatial autocorrelation of fires has to be taken into account when using the GLM technique for fire occurrence prediction. Paper VI showed that novel statistical predictive modelling techniques can be used to improve fire prediction, burned area estimation and fire risk mapping at a regional scale. However, some noticeable variation between different predictive modelling techniques for fire occurrence prediction and burned area estimation existed.
Resumo:
The use of UAVs for remote sensing tasks; e.g. agriculture, search and rescue is increasing. The ability for UAVs to autonomously find a target and perform on-board decision making, such as descending to a new altitude or landing next to a target is a desired capability. Computer-vision functionality allows the Unmanned Aerial Vehicle (UAV) to follow a designated flight plan, detect an object of interest, and change its planned path. In this paper we describe a low cost and an open source system where all image processing is achieved on-board the UAV using a Raspberry Pi 2 microprocessor interfaced with a camera. The Raspberry Pi and the autopilot are physically connected through serial and communicate via MAVProxy. The Raspberry Pi continuously monitors the flight path in real time through USB camera module. The algorithm checks whether the target is captured or not. If the target is detected, the position of the object in frame is represented in Cartesian coordinates and converted into estimate GPS coordinates. In parallel, the autopilot receives the target location approximate GPS and makes a decision to guide the UAV to a new location. This system also has potential uses in the field of Precision Agriculture, plant pest detection and disease outbreaks which cause detrimental financial damage to crop yields if not detected early on. Results show the algorithm is accurate to detect 99% of object of interest and the UAV is capable of navigation and doing on-board decision making.
Resumo:
In this paper a nonlinear control has been designed using the dynamic inversion approach for automatic landing of unmanned aerial vehicles (UAVs), along with associated path planning. This is a difficult problem because of light weight of UAVs and strong coupling between longitudinal and lateral modes. The landing maneuver of the UAV is divided into approach, glideslope and flare. In the approach UAV aligns with the centerline of the runway by heading angle correction. In glideslope and flare the UAV follows straight line and exponential curves respectively in the pitch plane with no lateral deviations. The glideslope and flare path are scheduled as a function of approach distance from runway. The trajectory parameters are calculated such that the sink rate at touchdown remains within specified bounds. It is also ensured that the transition from the glideslope to flare path is smooth by ensuring C-1 continuity at the transition. In the outer loop, the roll rate command is generated by assuring a coordinated turn in the alignment segment and by assuring zero bank angle in the glideslope and flare segments. The pitch rate command is generated from the error in altitude to control the deviations from the landing trajectory. The yaw rate command is generated from the required heading correction. In the inner loop, the aileron, elevator and rudder deflections are computed together to track the required body rate commands. Moreover, it is also ensured that the forward velocity of the UAV at the touch down remains close to a desired value by manipulating the thrust of the vehicle. A nonlinear six-DOF model, which has been developed from extensive wind-tunnel testing, is used both for control design as well as to validate it.
Resumo:
There is a growing interest to autonomously collect or manipulate objects in remote or unknown environments, such as mountains, gullies, bush-land, or rough terrain. There are several limitations of conventional methods using manned or remotely controlled aircraft. The capability of small Unmanned Aerial Vehicles (UAV) used in parallel with robotic manipulators could overcome some of these limitations. By enabling the autonomous exploration of both naturally hazardous environments, or areas which are biologically, chemically, or radioactively contaminated, it is possible to collect samples and data from such environments without directly exposing personnel to such risks. This paper covers the design, integration, and initial testing of a framework for outdoor mobile manipulation UAV. The framework is designed to allow further integration and testing of complex control theories, with the capability to operate outdoors in unknown environments. The results obtained act as a reference for the effectiveness of the integrated sensors and low-level control methods used for the preliminary testing, as well as identifying the key technologies needed for the development of an outdoor capable system.